1. Combining High - resolution satellite estimates with gauge observations
Soo-Hyun Yoo and Pingping Xie
Climate Prediction Center, NCEP/NWS/NOAA, Camp Springs, Maryland, USA
I. CMORPH Bias
Range Dependence
Bias as a function of CMORPH rainfall intensity over CONUS
Bias exhibits strong range dependence
Global Distribution
2000 – year annual mean precipitation
CMORPH captures the spatial distribution patterns very well
Bias exists
Over-estimates over tropical / sub-tropical areas
Under-estimates over mid-and high-latitudes
Time Scales of the Bias
Bias over CONUS
Bias presents substantial variations of
seasonal (top),
sub-monthly (middle),
year-to-year (bottom) time scales
II. Bias Correction
Annual Mean of
Strategy over Ocean
CMORPH: High-resolution with relatively short record
Pentad GPCP: Low-resolution with relatively homogeneous long record
Adjust the CMORPH against the pentad GPCP
- Match the PDF of CMORPH averaged to pentad / 2.5o lat/lon to that of pentad GPCP
General Strategy
Seasonal / Year-to-year variations in bias
 correction coefficients change with time
Sub-monthly variations in bias
 against sub-monthly gauge data
Range-dependence in bias
 PDF matching
Results over Global Land
2000 – 2009 annual mean
Large-scale bias corrected
Global Implementation for Daily Bias Correction
Step 1: Correction using Historical Data
- Establish PDF matching tables for each 0.25o lat/lon grid for each calendar date using data over nearby regions and over a period of ±15 days centering at the target date
Step 2: Correction using Real-Time Data
- Perform PDF matching using data over a 30-day period ending at the target date
Comparison over Africa
Application – Diurnal Cycle
JJA Mean of
Diurnal Cycle - Magnitude
CFSR captures the spatial distribution pattern of CMORPH well
Over-estimates over tropical / subtropical area
CFSR presents similar spatial distribution although under-estimate the magnitude of Diurnal Cycle
In CFSR, the phase of diurnal cycle over ocean is shifted about 3 -4 hour earlier than CMORPH
In CFSR, the phase of diurnal cycle overland is shifted about 3 -4 hour earlier than CMORPH
IV. Summary
III. Combining Satellite with Gauge
Example for Pakistan Flooding
We are in final stage of developing an operational system to construct gauge-satellite merged global precipitation analyses
Two sets of gauge-satellite precipitation analyses
Bias-corrected Satellite Estimates
Global
8kmx8km; 30-min
1998 to the present
Gauge-satellite combined analyses
Regional
0.25o lat/lon; daily
Diurnal cycle of precipitation is examined using the bias-corrected CMORPH and the CFSR data for a 6-year period from 2003 to 2008:
Overall, CFSR precipitation is capable of capturing the spatial distribution with reasonable quality, while the amount is over-estimated.
The magnitude of diurnal cycle in CFSR is mostly under-estimated over most of the ocean and land, except over-estimated over South and East Asian monsoon regions.
In CFSR, the phase of diurnal cycle over land and ocean is substantially shifted approximately 3~4 hour earlier than CMORPH.
Combining bias-corrected satellite estimates with daily gauge over the several regions
This is only possible for several regions due to different daily ending time in the gauge reports
Africa (06Z)
CONUS / Mexico (12Z)
S. America (12Z)
Australia (00Z)
China (00Z)
Combining the bias-corrected CMORPH with gauge observations through the Optimal Interpolation (OI) over selected regions where gauge observations have the same daily ending time
in which the CMORPH and gauge data are used as the first guess and observations, respectively
Gauge analysis depict heavy rain but tend to extend the raining area
Satellite data tend to under-estimate
Merged analysis present improved depiction of the heavy rain